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Semi-supervised bayesian classification of materials with impact-echo signals

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Semi-supervised bayesian classification of materials with impact-echo signals

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Igual García, J.; Salazar Afanador, A.; Safont Armero, G.; Vergara Domínguez, L. (2015). Semi-supervised bayesian classification of materials with impact-echo signals. Sensors. 15(5):11528-11550. doi:10.3390/s150511528

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/67602

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Title: Semi-supervised bayesian classification of materials with impact-echo signals
Author: Igual García, Jorge Salazar Afanador, Addisson Safont Armero, Gonzalo Vergara Domínguez, Luís
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Issued date:
Abstract:
[EN] The detection and identification of internal defects in a material require the use of some technology that translates the hidden interior damages into observable signals with different signature-defect correspondences. ...[+]
Subjects: Impact echo , Accelerometers , Mixture of Gaussians , Semi-supervised , Bayes classification
Copyrigths: Reconocimiento (by)
Source:
Sensors. (issn: 1424-8220 )
DOI: 10.3390/s150511528
Publisher:
MDPI
Publisher version: http://dx.doi.org/10.3390/s150511528
Project ID:
GV/PROMETEO II/2014/032
GV/ISIC/2012/006
GV/GV/2014/034
Thanks:
This work has been supported by Generalitat Valenciana under Grants PROMETEO II/2014/032, ISIC/2012/006 and GV/2014/034.
Type: Artículo

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